Image processing apparatus, image processing method, and storage medium

ABSTRACT

An apparatus includes a resolving unit configured to resolve input image data into image data for each frequency band, an acquisition unit configured to acquire skewness corresponding to the resolved image data resolved by the resolving unit, wherein the skewness is acquired from a histogram corresponding to each of the resolved image data, and an adjustment unit configured to determine image data to be processed, out of the resolved image data based on the acquired skewness acquired and perform gain adjustment on the determined image data.

BACKGROUND OF THE INVENTION Field of the Invention

The aspect of the embodiments relates to an image processing apparatus,an image processing method, and a storage medium that each performcontrol to express glossiness in an output image.

Description of the Related Art

In recent years, various approaches have been made in order to detecttexture such as transparency, gloss, and metallic feeling on a surfaceof an object, and express the detected texture on an image. JapanesePatent Application Laid-Open No. 2009-63694 discusses a technology ofdetermining whether an image includes a glossy part and performingcontrol so as to express a glossy image without lowering luminance ofthe entire image in order to control display of the image correspondingto an image signal in an image display apparatus including a backlight.As a gloss determination method for determining whether the imageincludes a glossy part, a method of calculating glossiness included inthe image with use of skewness of luminance histogram acquired fromimage data is used. The method is discussed in “Image statistics and theperception of surface qualities”, Nature 447, 206-209, (2007)(Non-patent Literature 1).

Non-patent Literature 1 discusses high correlation of physical gloss,brightness, and skewness of luminance histogram with perceptive glossand brightness through psychophysical experiment.

According to this correlation, for example, the luminance histogramacquired from the image data is skewed in a positive direction(appearance frequencies of pixels are gently spread toward higherluminance) as gloss on a surface of the image becomes higher.Accordingly, it is possible to evaluate glossiness on the surface of theimage based on the skewness of the luminance histogram.

On the other hand, it is desirable to express the texture (glossiness)in addition to color feeling and gradation also in an image printed byan image processing apparatus such as a multifunction peripheral and aprinter.

In a case where control to express glossiness in the image (glosscontrol) is performed, when gain adjustment is performed on imagesignals of all frequency bands (hereinafter, bands) in image data thatis determined as glossy, the gain of the image data in a band that doesnot require gain adjustment may be adjusted. For example, when the gainadjustment is performed on the image data that is determined as glossyand includes a low frequency and a high frequency, noise of ahigh-frequency component appears to be increased and gloss control onthe image may not be appropriately performed.

SUMMARY OF THE INVENTION

According to an aspect of the embodiments, an apparatus includes aresolving unit configured to resolve input image data into image datafor each frequency band, an acquisition unit configured to acquireskewness corresponding to the resolved image data resolved by theresolving unit, wherein the skewness is acquired from a histogramcorresponding to each of the resolved image data, and an adjustment unitconfigured to determine image data to be processed, out of the resolvedimage data based on the acquired skewness acquired by the acquisitionunit and perform gain adjustment on the determined image data.

Further features of the disclosure will become apparent from thefollowing description of exemplary embodiments with reference to theattached drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a block diagram illustrating an image processing systemaccording to an exemplary embodiment.

FIG. 2 is a diagram illustrating a configuration of a multifunctionperipheral (MFP) according to the present exemplary embodiment.

FIG. 3 is a block diagram illustrating a data processing unit accordingto a first exemplary embodiment.

FIG. 4 is a flowchart according to the first exemplary embodiment.

FIGS. 5A to 5D each illustrate an example of an input image according tothe first exemplary embodiment.

FIG. 6 is a diagram illustrating images in respective bands according tothe first exemplary embodiment.

FIG. 7 is a diagram illustrating a histogram of a B channel of the inputimage according to the first exemplary embodiment.

FIG. 8 is a diagram to explain band resolving according to the firstexemplary embodiment.

FIG. 9 is a diagram illustrating histograms of respective bandsaccording to the first exemplary embodiment.

FIG. 10 is a diagram illustrating skewness of the respective bandsaccording to the first exemplary embodiment.

FIG. 11 is a diagram to explain region division according to the firstexemplary embodiment.

FIG. 12 illustrates a user interface (UI) screen for gloss adjustmentaccording to the first exemplary embodiment.

FIG. 13 is a diagram illustrating images of the respective bandsaccording to the first exemplary embodiment.

FIG. 14 is a diagram illustrating resultant images after glossadjustment according to the first exemplary embodiment.

FIG. 15 is a block diagram illustrating a data processing unit 215according to a second exemplary embodiment and a third exemplaryembodiment.

FIG. 16 is a flowchart according to the second exemplary embodiment.

FIG. 17 is a flowchart according to the third exemplary embodiment.

FIG. 18 is a UI screen for gloss adjustment according to the secondexemplary embodiment.

FIG. 19 is a UI screen for gloss adjustment according to the thirdexemplary embodiment.

FIGS. 20A to 20D are explanatory diagrams of the gloss adjustmentaccording to the second exemplary embodiment and the third exemplaryembodiment.

FIG. 21 is a diagram illustrating resultant images after the glossadjustment according to the second exemplary embodiment and the thirdexemplary embodiment.

FIGS. 22A to 22C are explanatory diagrams of saturated pixel calculationaccording to the third exemplary embodiment.

DESCRIPTION OF THE EMBODIMENTS

Exemplary embodiments of the disclosure are described below withreference to drawings.

A first exemplary embodiment is described below. In FIG. 1, amultifunction peripheral (MFP) 101 that achieves a plurality of kinds offunctions (e.g., copy function, print function, and transmissionfunction) is connected to a local area network (LAN) 102 built in anoffice A. The LAN 102 is also connected to an external network 104through a proxy server 103. A client personal computer (PC) 100 receivesdata transmitted from the MFP 101 and uses the functions of the MFP 101through the LAN 102. For example, the client PC 100 transmits print datato the MFP 101 to make a print document based on the print data by theMFP 101. The configuration in FIG. 1 is an example, and a plurality ofoffices including components similar to those of the office A may beconnected to the external network 104. Further, the external network 104is typically a communication network that is realized by, for example,the Internet, a LAN, a wide area network (WAN), a telephone line, adedicated digital line, an asynchronous transfer mode (ATM) line, aframe relay line, a satellite communication line, a cable televisionline, and a radio line for data broadcasting. Any communication networkis usable as long as the communication network can perform datatransmission/reception. Further, various kinds of terminals of theclient PC 100 and the proxy server 103 include standard components to bemounted on a general purpose computer. Examples of the standardcomponents include a central processing unit (CPU), a random accessmemory (RAM), a read-only memory (ROM), a hard disk drive, an externalstorage device, a network interface, a display, a keyboard, and a mousethat are not illustrated.

FIG. 2 is a diagram illustrating a detailed configuration of the MFP101. The MFP 101 includes a scanner unit 201 serving as an image datainput device, a printer unit 202 serving as an image data output device,a control unit 204 controlling the whole of the MFP 101, and anoperation unit 203 serving as a user interface. The control unit 204 isa controller that performs input/output of image information and deviceinformation by connecting to the scanner unit 201, the printer unit 202,and the operation unit 203, and a LAN 209 on the other side. A CPU 205is a processor that controls the whole of the system. A RAM 206 servesas a system work memory for operation of the CPU 205, and also serves asan image memory to temporarily hold image data. A ROM 210 is a boot ROMthat holds programs such as a boot program of the system. A storage unit211 is a nonvolatile storage device such as a hard disk drive, and holdssystem control software and image data. An operation unit interface(I/F) 207 is an interface unit working with the operation unit (UI) 203,and provides, to the operation unit 203, image data to be displayed onthe operation unit 203. Further, the operation unit I/F 207 transmits,to the CPU 205, information instructed by a user of the image processingapparatus through the operation unit 203. A network I/F 208 connects theimage processing apparatus to the LAN 209, and performs input/output ofdata (e.g., transmits and receives binary image data to and from otherapparatus). The above-described devices are disposed on a system bus216.

Further, an image bus interface 212 is a bus bridge that connects thesystem bus 216 and an image data bus 217 and converts a data structure.The image data bus 217 transfers image data at high speed. For example,the image data bus 217 includes a peripheral component interconnect(PCI) bus or conforms to IEEE1394. The following devices are disposed onthe image data bus 217. A raster image processor (RIP) 213 realizesso-called rendering processing of analyzing a page description language(PDL) code and developing the PDL code into a bitmap image withspecified resolution. A device I/F 214 is connected to the scanner unit201 as the image data input device through a signal line 218, and to theprinter unit 202 as the image data output device through a signal line219. The device I/F 214 performs conversion of synchronous/asynchronoussystem of image data. A data processing unit 215 performs glossdetermination and gloss control of image data.

Further, the data processing unit 215 may decompress compressed datareceived through the network I/F 208 and the LAN 209. The decompressedimage is transmitted to the printer unit 202 through the device I/F 214,and is printed. The data processing unit 215 is described in detailbelow.

<Description of Data Processing Unit 215>

Next, a configuration of each of a gloss determination unit and a glosscontrol unit realized by the data processing unit 215 in FIG. 2 isdescribed with reference to a block diagram in FIG. 3. The dataprocessing unit 215 may function as each processing unit in FIG. 3 whenthe processor executes a computer program, or a part or all of theprocessing units may be configured by hardware such as an applicationspecific integrated circuit (ASIC) and an electronic circuit.

A region dividing unit 301 divides input image data into rectangularunits or into regions in optional shapes. FIG. 11 illustrates an examplein a case where the input image data is divided into rectangular units.FIG. 11 is a schematic diagram of the input image data having a width Wand a height H. The region dividing unit 301 divides the input imagedata into rectangular units having a width w and a height h. An examplein which an image of an orange as a fruit is used as the input imagedata is described below with reference to FIGS. 5A to 5D.

A channel resolving unit 302 performs channel resolving on each regionof the color image data divided by the region dividing unit 301. In thepresent exemplary embodiment, as the channel resolving, resolving ofeach region of the color image data into components of three colors R,G, and B is described; however, the channel resolving is not limitedthereto, and each region may be resolved into, for example, colorcomponents of LaB or YUV.

A band resolving unit 303 resolves each image data of all channelsresolved by the channel resolving unit 302, into image data of aplurality of different frequency bands.

The band resolving according to the present exemplary embodiment isdescribed with reference to FIG. 8. Input image data 801 indicates imagedata as a target of channel resolving by the channel resolving unit 302.Smoothing filters 803 to 806 are smoothing filters (low-pass filters) 1to 4, and each perform, on the input image data 801, filter processingcorresponding to a smoothing degree of each filter. The smoothing degreeis a degree of processing (smoothing processing) for smoothing avariation by reducing a difference of signal values included in theimage data. The processing is performed such that the variation of eachsignal value included in the image data is more smoothed as thesmoothing degree becomes larger. Among the smoothing filters 1 to 4, thesmoothing filter 1 is a smoothing filter with the weakest smoothingdegree, and the smoothing filter 4 is a smoothing filter with thestrongest smoothing degree. The smoothing degree is increased in orderof the smoothing filters 1, 2, 3, and 4.

Each of the smoothing filters is not limited to the low-pass filter, andmay be an edge-preserving smoothing filter (bilateral filter or guidedfilter).

Reference numerals 807 to 810 indicate calculation of a difference ofthe signal values included in the image data processed by the smoothingfilters described above. First, a difference 807 between the signalvalue included in the input image data and the signal value of the imagedata processed by the smoothing filter 1 is calculated to obtain imagedata of a band 0 from the process target image data. Next, a difference808 between the signal value included in the image data processed by thesmoothing filter 1 and the signal value included in the image dataprocessed by the smoothing filter 2 is calculated to obtain image dataof a band 1 from the process target image data. Subsequently, image dataof a band 2 and image data of a band 3 are obtained from the processtarget image data in a similar manner. Among the bands 0 to 3, the imagedata of the band 0 is the image data of the highest band (highfrequency) out of the process target image data, and the image data ofthe band 3 is the image data of the lowest band (low frequency) out ofthe process target image data. The band of the image data becomes lowerin order of the bands 0, 1, 2, and 3.

Reference image data 802 is image data used for band compositiondescribed below. Accordingly, the input image data 801 is obtained byadding, to the reference image data 802, the image data of the band 0,the image data of the band 1, the image data of the band 2, and theimage data of the band 3.

As described above, the band resolving unit 303 resolves the input imagedata to be processed, into image data of the plurality of differentbands. The band resolving may be performed by a well-known method suchas wavelet transformation.

A histogram generation unit 304 generates a histogram of the image datain each of the bands resolved by the band resolving unit 303. In thisexample, the histogram indicates frequency distribution in which alateral axis indicates an image signal value or a signal valuedifference, and a vertical axis indicates a frequency.

A skewness calculation unit 305 acquires skewness for each channel/bandfrom the histogram generated by the histogram generation unit 304. Theskewness may be acquired with use of a common numerical expression asrepresented by, for example, the following expression 1.

Skewness=Σ(Xi−Xave)³ /N×S ³  (Expression 1)

where N is the number of pieces of data, Xi is a value of each data,Xave is an arithmetic average, and S is a standard deviation.

The skewness indicates a degree of skew of a graph. When the skewness isa positive value larger than zero, the graph is shifted to left. Incontrast, when the skewness is a negative value smaller than zero, thegraph is shifted to right. In the case of no shift, the graph has normaldistribution.

In a case where the skewness of the histogram obtained from the imagedata has a positive value, it is determined that the image correspondingto the image data is glossy. In contrast, in a case where the skewnessof the histogram obtained from the image data has a negative value, itis determined that the image corresponding to the image data is notglossy.

A gloss determination unit 306 determines whether the process targetimage data is image data including a gloss region, based on the skewnessfor each channel/band obtained by the skewness calculation unit 305.

In the present exemplary embodiment, since the band resolving isperformed by the band resolving unit 303, it is determined whether aregion is glossy based on each band. When it is determined that theregion is glossy in a band in at least one of R, G, and B channels, itis determined that the image corresponding to the image data of therelevant band in the R, G, and B channels includes a gloss region.

A gain adjustment unit 307 multiplies a pixel signal included in theimage data of each band resolved by the band resolving unit 303, by apredetermined coefficient based on the determination result of the glossdetermination unit 306. As a result, the gain adjustment is performed onthe image data. In one embodiment the gain adjustment is performed onthe image data of the same band in all of the RGB channels. If the gainadjustment is performed only on the image data of one band in onechannel, color balance in the input image data after the adjustment islost.

The predetermined coefficient in the gain adjustment is a positivevalue. For example, in a case where the coefficient is larger than one,the signal value of the image data is amplified. Accordingly, glossinessexpressed by the image is increased (gloss up). In contrast, in a casewhere the predetermined coefficient in the gain adjustment is smallerthan one, the signal value is reduced. As a result, the glossinessexpressed by the image is suppressed (gloss down).

FIG. 12 is a UI screen for gloss adjustment according to the presentexemplary embodiment, and the UI screen is displayed on the operationunit 203 in FIG. 2. A setting value for gloss adjustment is previouslydesignated by an operator, for example, when image data held by theclient PC 100 or the image data held by the storage unit 211 is printed.

When a setting value “+1” or “+2” is designated by the operator, thedesignation indicates gloss up. As a result, glossiness expressed by aregion that has been determined as the gloss region included in theimage to be processed, is increased. When a setting value “4” or “−2” isdesignated, the designation indicates gloss down. As a result,glossiness expressed by the region that has been determined as the glossregion included in the image to be processed, is suppressed. An exampleof a fruit in which an image of “orange” is used as the input image datais described below with reference to FIG. 14.

The coefficients for gain adjustment corresponding to the setting values“−2” to “+2” of the gloss adjustment are, for example, “0.6”, “0.8”,“1.0”, “1.2”, and “1.4”, respectively; however, the coefficients are notlimited thereto.

A band synthesizing unit 308 synthesizes the image data of the bandsubjected to the gain adjustment by the gain adjustment unit 307, theimage data of the band that has been determined as nonglossy (notincluding gloss region) by the gloss determination unit 306, and thereference image data obtained through resolving by the band resolvingunit 303. As a result, the band synthesizing unit 308 generates outputimage data.

FIG. 4 is a flowchart for explaining the gloss determination and thegloss control by the data processing unit 215. A program that executesthe flowchart is held by the ROM 210 or the storage unit 211 in FIG. 2,and is executed by the CPU 205. The CPU 205 can exchange data with thedata processing unit 215 through the image bus interface 212, the systembus 216, and the image data bus 217. Further, description will be givenby appropriately referring to FIG. 5A to FIG. 10. FIG. 5A illustrates anexample of the input image data according to the present exemplaryembodiment, and a region 501 represents an image of “orange” as a fruit.A color of the image is orange, and a surface of the image presents aglossy state. A region 502 represents a background image and a colorthereof is white.

First, in step S401, the region dividing unit 301 divides the entireregion of input image data 500 obtained by receiving the input image,into rectangular units or into regions in optional shapes. FIG. 5Billustrates an example in which the input image data 500 illustrated inFIG. 5A is divided into rectangular units. In FIG. 5B, the input imagedata 500 is divided into rectangular units as illustrated by regions 503to 511. Accordingly, for example, the region 507 includes only a regionrepresenting “orange” of the fruit, whereas the region 510 includes animage region representing “orange” of the fruit and a regionrepresenting the background image in a mixed state.

On the other hand, a known method may be used to divide the region intoregions in optional shapes. For example, regions of similar colors maybe continuously integrated to finally form one region of similar colors.FIG. 5C illustrates an example in which the input image data 500 asillustrated in FIG. 5A is divided into regions in optional shapes. InFIG. 5C, the input image data 500 is divided into regions in optionalshapes as illustrated by regions 512 to 518. Therefore, for example, theimage can be divided into a region representing “orange” of the fruitand a region representing the background image. When this method isused, however, processing load may become larger than the method ofdividing the region into rectangular units, and processing accuracy maybe deteriorated. In the present exemplary embodiment, the processing ofdividing the input image data into rectangular units is used. Each ofthe rectangular units may have an optional size.

Next, in step S402, the channel resolving unit 302 performs channelresolving on each of the regions of the color image data divided by theregion dividing unit 301. FIG. 5D illustrates a state where the imagedata in FIG. 5B is divided into image data of three color components ofan R component, a G component, and a B component. In actual processing,it is unnecessary to generate image data resolved into the three colorcomponents of the R component, the G component, and the B component asillustrated in FIG. 5D, and it is sufficient to refer to signal valuesof each of the R, G, and B color components from the image data dividedinto the rectangular units in FIG. 5B.

Next, in step S403, the band resolving unit 303 resolves the image dataof all channels resolved in step S402, into image data of differentbands.

FIG. 6 is a schematic diagram illustrating, as an example, a state wherethe input image data of one channel is resolved into image data of somebands. Image data 601 corresponds to a rectangle at a center of theimage data of the B channel in FIG. 5D. Image data 602 to 605respectively correspond to image data of bands 0 to 3 that are obtainedby resolving the image data 601 as the input image data by the bandresolving unit 303. The image data 602 indicates the image data of theband 0 in FIG. 8, the image data 603 indicates the image data of theband 1 in FIG. 8, the image data 604 indicates the image data of theband 2 in FIG. 8, and the image data 605 indicates the image data of theband 3 in FIG. 8.

Vertical and lateral dashed lines in each of the image data 602 to 605in the figure schematically represent a level of a frequency. The imagedata of the band 0 is the image data of the highest band (highfrequency) of the input image data, and the image data of the band 3 isthe image data of the lowest band (low frequency) of the input imagedata.

FIG. 13 illustrates an example in which the band resolving is performedon an actual image of “orange” of the fruit. As with FIG. 6, image data1302 to 1305 indicate image data of the band 0 to 3 that are obtained byresolving image data 1301 as the input image data by the band resolvingunit 303.

The band resolution corresponds to a difference of image data obtainedby performing processing using the smoothing filters on the input imagedata. Accordingly, each band includes a negative value. In this example,the image data 602 to 605 are corrected to positive values of 8 bits (0to 255) in order to facilitate visual understanding. Further, althoughnot illustrated, the band resolving is similarly performed on the imagedata of the R channel and the image data of the G channel. The method ofthe band resolving is described above and its description is omitted.

Next, in step S404, the histogram generation unit 304 generate ahistogram with respect to the image data of each band resolved in stepS403. In other words, the histogram is generated from the image data ofeach band in FIG. 6. Histograms 901 to 904 illustrated in FIG. 9 arehistograms respectively generated from image data of the bands 0 to 3 inFIG. 6. In this example, a lateral axis indicates a signal valuedifference and has a range of −128 to +128. Further, a vertical axisindicates a frequency of an image signal value.

It can be seen that the histograms acquired from the image data of theband 0 and the image data of the band 1 in the high-frequency band areskewed in a negative direction, and the histograms acquired from theimage data of the band 2 and the image data of the band 3 in thelow-frequency band are skewed in a positive direction.

As a comparison, FIG. 7 illustrates a histogram acquired from the inputimage data 601 before the band resolving is performed in FIG. 6. Asillustrated in FIG. 7, the histogram acquired from the image data beforethe band resolving is skewed in a positive direction. As illustrated inFIG. 9, however, it can be seen from the histograms acquired from theimage data of the respective bands that the input image data includesthe image data of the bands 0 and 1 skewed in the negative direction andthe image data of the bands 2 and 3 skewed in the positive direction.

Next, in step S405, the skewness calculation unit 305 acquires skewnessfrom each of the histograms generated in step S404. The method ofacquiring the skewness is as described above. FIG. 10 illustratesskewness acquired from the respective histograms 901 to 904 in FIG. 9.As described above, it can be seen that the skewness corresponding tothe image data of the bands 0 and 1 of the histogram skewed in thenegative direction has a negative value, and the skewness correspondingto the image data of the bands 2 and 3 of the histogram skewed in thepositive direction has a positive value.

Next, in step S406, the gloss determination unit 306 determines whetherthe image data to be processed includes a gloss region, based on theskewness acquired in step S405. In the present exemplary embodiment,since the band resolving is performed in step S403, it is determinedwhether the image data of each band includes a gloss region in the imagedata to be processed. When the skewness has a positive value, it may bedetermined that the image data to be processed includes a gloss region.When the skewness has a negative value, it may be determined that theimage data to be processed does not include a gloss region. Further, athreshold of the skewness used for the gloss determination may beoptionally changed depending on a state of the printer unit in the imageprocessing apparatus or a kind of a sheet or toner to be used. Further,it may be determined that the image data of the band having the highestskewness includes a gloss region.

In the present exemplary embodiment, it is determined in step S407 thatthe image data to be processed includes a gloss region when the skewnessis larger than a predetermined threshold, and it is determined in stepS408 that the image data to be processed does not include a gloss regionwhen the skewness is equal to or lower than the predetermined threshold.For example, when the predetermined threshold is set to “1.0”, the glossdetermination unit 306 determines that the image data of the band 3includes a gloss region and the image data of the bands 0 to 2 does notinclude a gloss region, through comparison with the skewness in FIG. 10.

Next, in step S409, the gain adjustment unit 307 determines the imagedata of the band that has been determined in step S407 as including agloss region, as a process target, and performs the gain adjustment onthe image data.

In step S406, it is determined that the image data of the band 3includes a gloss region. Accordingly, the gain adjustment unit 307performs the gain adjustment of the image data of the band 3 bymultiplying the image data by a predetermined coefficient based on thesetting value “−2” to “+2” of the gloss adjustment indicated on the UIscreen in FIG. 12. For example, when the setting value is “+2”, the gainadjustment unit 307 multiplies the image data of the band 3 by acoefficient “1.4”. On the other hand, the gain adjustment is notperformed on the image data of the bands 0 to 2 that has been determinedas not including a gloss region in step S408.

FIG. 14 illustrates examples of a resultant image after the glossadjustment is performed on the input image data.

Images 1401 to 1405 in FIG. 14 are resultant images when the settingvalues “−2” to “+2” are selected, respectively, and are output imagesafter band synthesis described below.

It can be seen that, when the setting value “+1” or “+2” is designated,the image 1404 or the image 1405 is generated and glossiness of thegloss region is increased. In contrast, it can be seen that, when thesetting value “−2” or “−1” is designated, the image 1401 or the image1402 is generated and glossiness of the gloss region is reduced.

Next, in step S410, the band synthesizing unit 308 synthesizes the imagedata of the band subjected to the gain adjustment in step S409, theimage data of the band determined as not including a gloss region instep S408, and the reference image data obtained through the bandresolving by the band resolving unit 303. The synthesized image data isgenerated as the output image data.

As described above, when the gloss control is performed on the imagedata to be processed for each frequency band, the gain adjustment isperformed on the band requiring the gain adjustment of the image to beprocessed, and the gain adjustment is not performed on the band notrequiring the gain adjustment. This allows for the gloss control withhigh precision.

In the present exemplary embodiment, the band resolving is performed onthe image data including all channels resolved by the channel resolvingunit 302, to resolve the image data into the image data of the pluralityof different frequency bands. The band resolving, however, is notlimited thereto, and the band resolving may be performed only on theimage data including a channel determined as including a gloss region,after the channel resolving is performed.

As a result, the band resolving is performed on the image data of eachresolved channel, which makes it possible to accelerate the processingas compared with a case where the gloss determination processing and thegloss control are performed on the image data of each resolved band.

A second exemplary embodiment is described below. In the first exemplaryembodiment, the example has been described in which the gain adjustmentis performed on the image data of the frequency band including theskewness larger than the predetermined threshold, with respect to theimage data to be subjected to the gloss control, to enable the glosscontrol with high precision.

In the second exemplary embodiment, “gain adjustment” and “rangeadjustment” are performed based on setting of “gloss intensity” and“gloss range” designated by the operator through an UI for glossadjustment in FIG. 18 as described below. This makes it possible toperform the gloss adjustment on the image data more precisely in orderto represent the glossiness intended by the user when the input image isoutput.

First, a block diagram according to the second exemplary embodiment isdescribed with reference to FIG. 15. Description of the parts alreadydescribed in the first exemplary embodiment is omitted. A differencefrom FIG. 3 is a gloss adjustment unit 1501. The gloss adjustment unit1501 includes a gain adjustment unit 1502 and a range adjustment unit1503.

The gain adjustment unit 1502 adjusts the image signal value of thepixel to be processed, by multiplying the image data of the frequencyband including the skewness higher than the predetermined threshold bythe predetermined coefficient, in a manner similar to the gainadjustment unit 307 described in the first exemplary embodiment.

The range adjustment unit 1503 performs adjustment by fixing the gaincoefficient and increasing the number of processed bands to bemultiplied by the gain coefficient. In other words, out of theband-resolved image data, the number of pieces of image data to bemultiplied by the gain coefficient is increased. For example, in a casewhere the band of the image data is resolved into the bands 0 to 3 bythe band resolving unit 303, the maximum number of processed bandsbecomes “4” (number of pieces of image data to be processed is four).When the number of bands to be processed is increased in theabove-described manner, the number of pieces of image data to beprocessed out of the band-divided image data is increased. This makes itpossible to increase the number of pixels as targets of the gainadjustment out of the pixels configuring the input image. In otherwords, a region (range) of the input image where the gloss is adjustedbecomes larger.

Next, the UI screen for the gloss adjustment according to the secondexemplary embodiment is described with reference to FIG. 18. The UIscreen is displayed on the operation unit 203 in FIG. 2.

A UI of “gloss intensity” 1801 is a UI for adjusting the image signalvalue of the pixel to be processed, by the gain adjustment unit 1502.FIG. 20A illustrates examples of the coefficient for the gain adjustmentcorresponding to the setting values “0” to “+2”.

A UI of “gloss range” 1802 is a UI for adjusting through increase of thenumber of bands to be processed, by the range adjustment unit 1503. FIG.20B illustrates examples of the number of processed bands correspondingto the setting values “0” and “+1”.

When the gloss range is set to “0”, the number of processed bands is“1”, and the band to be processed is “band of the highest skewness”. Forexample, in a case where the skewness for the respective bandsillustrated in FIG. 10 are obtained, when the threshold of the skewnessused for the gloss determination is set to “0”, it is determined thatthe image data of the band 2 and the image data of the band 3 include agloss region. The image data of the band of the highest skewness is theimage data of the band 3, and the image data of the band 3 becomes thetarget image data of the band to be multiplied by the gain coefficient.

When the gloss range is set to “+1”, the number of processed bands is“2”, and the band to be processed includes “band of the highestskewness” and “band adjacent to band of the highest skewness”.

Likewise, in the case where the skewness for the respective bandsillustrated in FIG. 10 are obtained, the image data of two bands,namely, the image data of the band 3 and the image data of the band 2become the target image data to be multiplied by the gain coefficient.

Next, a flowchart according to the second exemplary embodiment isdescribed with reference to FIG. 16.

FIG. 16 is a flowchart to describe the gloss determination and the glosscontrol by the data processing unit 215. A program executing theflowchart is stored in the ROM 210 or the storage unit 211 in FIG. 2,and is executed by the CPU 205. The CPU 205 can exchange data with thedata processing unit 215 through the image bus interface 212, the systembus 216, and the image data bus 217. Description of the parts alreadydescribed with reference to FIG. 4 in the first exemplary embodiment isomitted.

First, in step S1601, the operation unit 203 receives a settinginstruction of the gloss adjustment by the operator, more specifically,receives a setting instruction of “gloss intensity” and “gloss range”described with reference to FIG. 18.

Next, the processing in steps S401 to S408 described with reference toFIG. 4 are performed.

Next, in step S1602, the gloss adjustment unit 1501 determines whetherthe setting received by the operation unit 203 in step S1601 is asetting for “gloss intensity” or “gloss range”.

In a case where “gloss intensity” is set (gloss intensity in stepS1602), the gain adjustment unit 1502 adjusts the image signal value ofthe pixel to be processed through multiplication by a predeterminedcoefficient in step S1603.

In a case where “gloss range” is set (gloss range in step S1602), therange adjustment unit 1503 performs the adjustment, in step S1604, byfixing the gain coefficient and increasing the number of bands to beprocessed out of the band-resolved image data.

In a case where both of “gloss intensity” and “gloss range” are set,both of the gain adjustment in step S1603 and the range adjustment instep S1604 are performed (not illustrated).

Next, the processing in step S410 described above with reference to FIG.4 is performed.

According to the second exemplary embodiment, “gain adjustment” and“range adjustment” are performed based on the setting of “glossintensity” or “gloss range”. In other words, the gain coefficient usedin the gloss adjustment and the number of pieces of image data to beadjusted out of the band-resolved image data are changeable. This makesit possible to precisely perform the gloss adjustment on the image dataas the target of the gloss control in order to express the glossinessintended by the user.

A third exemplary embodiment is described below. In the third exemplaryembodiment, a method of performing the gloss adjustment whilesuppressing white void caused by the gain adjustment, based on thesetting of “gloss adjustment” designated by the operator through a UIfor the gloss adjustment in FIG. 19 described below, is described.

For example, when the gloss adjustment is set to “0”, “+1”, or “+2”, thegloss is stepwisely increased through the gain adjustment. Images 2001to 2003 in FIG. 21 respectively correspond to the setting of the glossadjustment of “0”, “+1”, and “+2”, and illustrate states where the glossis stepwisely increased through the gain adjustment.

When the gloss adjustment is set to “+3”, the number of white-saturatedpixels is increased, which results in an unfavorable image includingwhite void. An image 2104 in FIG. 21 illustrates a state where whitevoid occurs on the gloss-adjusted image due to the gain adjustment.

Accordingly, in a case where the number of the white-saturated pixelsbecomes larger than a predetermined threshold, the number of bands to beadjusted (number of pieces of image data of band to be processed out ofband-resolved image data) is adjusted without increasing the coefficientof the gain adjustment. Thus, the gloss adjustment is performed whilesuppressing white void caused by the gain adjustment.

An image 2105 in FIG. 21 corresponds to the setting “+3” of the glossadjustment, and illustrates a state where the range adjustment isperformed while the gain coefficient is fixed to the coefficient for thesetting “+2” of the gloss adjustment.

Next, a UI screen for the gloss adjustment according to the thirdexemplary embodiment is described with reference to FIG. 19. The UIscreen is displayed on the operation unit 203 in FIG. 2.

FIGS. 20C and 20D illustrate examples of the coefficients for the gainadjustment corresponding to the setting values “0” to “+3” and the bandrange of the image data (number of processed bands) as the target of thegain adjustment. FIG. 20C illustrates initial values of relationshipbetween the setting value of the gloss adjustment, the gain coefficient,and the number of processed bands. FIG. 20D illustrates a case where thenumber of white-saturated pixels becomes larger than the predeterminedthreshold when the gloss adjustment is set to “+3”. More specifically,when the gloss adjustment is set to “+3” and an initial value “1.6” ofthe gain coefficient is used, the number of white-saturated pixelsbecomes larger than the predetermined threshold. Accordingly, the numberof processed bands is increased to “2” while the gain coefficient isfixed to “1.4” as with the case where the gloss adjustment is set to“+2”.

Next, a flowchart according to the third exemplary embodiment isdescribed with reference to FIG. 17.

FIG. 17 is a flowchart for describing the gloss determination and thegloss control by the data processing unit 215. A program executing theflowchart is stored in the ROM 210 or the storage unit 211 in FIG. 2,and is executed by the CPU 205. The CPU 205 can exchange data with thedata processing unit 215 through the image bus interface 212, the systembus 216, and the image data bus 217. Description of the parts alreadydescribed with reference to FIG. 4 in the first exemplary embodiment isomitted.

First, in step S1701, the operation unit 203 receives the settinginstruction of the gloss adjustment by the operator described above withreference to FIG. 18.

Next, the processing in step S401 to S408 described above with referenceto FIG. 4 are performed.

Next, in step S1702, the gloss adjustment unit 1501 calculates anincrement amount of the saturated pixels in a region that has beendetermined as the gloss region in step S407, from the setting value ofthe gloss adjustment in step S1701 and the coefficient for the gainadjustment.

The calculation of the increment amount of the saturated pixels isdescribed with reference to FIGS. 22A to 22C. The description is madewith use of simple values to facilitate understanding of thedescription.

FIG. 22A illustrates a histogram (relationship between signal value andfrequency) of the region determined as the gloss region, before the gainadjustment is performed. In this example, a signal value 0 correspondsto a black pixel, and a signal value 255 corresponds to a white pixel.In this case, the frequency of the white pixel before the gainadjustment is 100.

FIG. 22B illustrates a histogram (relationship between signal value andfrequency) after the gain adjustment with the gain coefficient of 1.2 isperformed on the image data. The frequency of the white pixel after thegain adjustment is 100 that is the same as the frequency before the gainadjustment.

FIG. 22C illustrates a histogram (relationship between signal value andfrequency) after the gain adjustment is performed with the gaincoefficient of 1.6 on the image data. The frequency of the pixel withthe signal value of 200 is 300 before the gain adjustment. When pixelsconfiguring the image data are multiplied by the gain coefficient of1.6, all the signal values of the pixels become 255. As a result, thefrequency of the white pixel after the gain adjustment becomes 400 intotal, by adding 100 for the white pixel before the gain adjustment.

Accordingly, in the example in FIGS. 22A to 22C, the increment amount ofthe saturated pixels is “0” when the gain coefficient is 1.2 and is“300” when the gain coefficient is 1.6.

When the predetermined threshold for determining the increment amount ofthe saturated pixels is set to 200, the gain adjustment is performedwhen the gain coefficient is 1.2, and the band adjustment is performedwhen the gain coefficient is 1.6.

The increment amount of the saturated pixels is determined based on theincrement amount of the frequency of the white pixels in the presentcase; however, the determination of the increment amount is not limitedthereto. For example, the determination may be made based on a ratio ofthe white pixels to the region determined as the gloss region.

Next, in step S1703, the gloss adjustment unit 1501 determines whetherthe increment amount of the saturated pixels calculated in step S1702 islarger than the predetermined threshold.

In a case where the increment amount is equal to or lower than thethreshold (NO in step S1704), the gain adjustment unit 1502 adjusts theimage signal value of the pixel to be processed through multiplicationby a predetermined coefficient in step S1704. In a case where theincrement amount is larger than the threshold, the range adjustment unit1503 performs the adjustment, in step S1705, by fixing the gaincoefficient and increasing the number of processed bands.

Next, the processing in step S410 described above with reference to FIG.4 is performed.

According to the third exemplary embodiment, it is possible to performthe gloss adjustment on the image data as the target of the glosscontrol based on the setting of “gloss adjustment” while suppressingwhite void caused by the gain adjustment.

Other Embodiments

Embodiment(s) of the disclosure can also be realized by a computer of asystem or apparatus that reads out and executes computer executableinstructions (e.g., one or more programs) recorded on a storage medium(which may also be referred to more fully as a ‘non-transitorycomputer-readable storage medium’) to perform the functions of one ormore of the above-described embodiment(s) and/or that includes one ormore circuits (e.g., application specific integrated circuit (ASIC)) forperforming the functions of one or more of the above-describedembodiment(s), and by a method performed by the computer of the systemor apparatus by, for example, reading out and executing the computerexecutable instructions from the storage medium to perform the functionsof one or more of the above-described embodiment(s) and/or controllingthe one or more circuits to perform the functions of one or more of theabove-described embodiment(s). The computer may comprise one or moreprocessors (e.g., central processing unit (CPU), micro processing unit(MPU)) and may include a network of separate computers or separateprocessors to read out and execute the computer executable instructions.The computer executable instructions may be provided to the computer,for example, from a network or the storage medium. The storage mediummay include, for example, one or more of a hard disk, a random-accessmemory (RAM), a read only memory (ROM), a storage of distributedcomputing systems, an optical disk (such as a compact disc (CD), digitalversatile disc (DVD), or Blu-ray Disc (BD)™), a flash memory device, amemory card, and the like.

While the disclosure has been described with reference to exemplaryembodiments, it is to be understood that the disclosure is not limitedto the disclosed exemplary embodiments. The scope of the followingclaims is to be accorded the broadest interpretation so as to encompassall such modifications and equivalent structures and functions.

This application claims the benefit of Japanese Patent Applications No.2017-178107, filed Sep. 15, 2017, and No. 2018-065506, filed Mar. 29,2018, which are hereby incorporated by reference herein in theirentirety.

What is claimed is:
 1. An apparatus, comprising: a resolving unitconfigured to resolve input image data into image data for eachfrequency band; an acquisition unit configured to acquire skewnesscorresponding to the resolved image data resolved by the resolving unit,wherein the skewness is acquired from a histogram corresponding to eachof the resolved image data; and an adjustment unit configured todetermine image data to be processed, of the resolved image data basedon the acquired skewness and perform gain adjustment on the determinedimage data.
 2. The apparatus according to claim 1, further comprising: asynthesizing unit configured to synthesize the input image data, theimage data obtained by performing gain adjustment using the adjustmentunit on the image data to be processed, out of the resolved image data,and the image data not to be processed out of the resolved image data;and an output unit configured to output the synthesized image data. 3.The apparatus according to claim 1, wherein the input image data isdivided into optional regions, and the resolving unit performs resolvingon each of the divided regions.
 4. The apparatus according to claim 1,wherein the input image data is image data resolved into at least twocolor components.
 5. The apparatus according to claim 1, wherein theresolving unit resolves the input image data into a plurality of imageswith different frequencies with use of smoothing filters.
 6. Theapparatus according to claim 1, wherein the histogram is frequencydistribution indicating frequencies of pixels with respect to imagesignal values of the input image data.
 7. The apparatus according toclaim 1, wherein the skewness of the histogram is a value indicating adegree of skew of the histogram.
 8. The apparatus according to claim 1,wherein the adjustment unit performs the gain adjustment by multiplyingeach of the resolved bands by a predetermined coefficient in a casewhere the skewness calculated for each of the bands is larger than apredetermined threshold.
 9. The apparatus according to claim 1, whereina gain coefficient used when the gain adjustment is performed on theimage data by the adjustment unit can be changed.
 10. The apparatusaccording to claim 9, further comprising a display control unitconfigured to perform display to previously designate the gaincoefficient.
 11. The apparatus according to claim 1, wherein number ofpieces of image data to be processed, out of the resolved image data,can be changed based on the acquired skewness.
 12. The apparatusaccording to claim 11, further comprising a display control unitconfigured to perform display to previously designate number of piecesof image data.
 13. The apparatus according to claim 1, furthercomprising a control unit configured to control a gain coefficient usedwhen the gain adjustment is performed on the image data and to controlnumber of pieces of image data to be adjusted, wherein the control unitdetermines the gain coefficient in the gain adjustment and the number ofpieces of image data to be adjusted, with use of a result of acomparison between number of white pixels included in the image databefore the adjustment is performed and the number of white pixelsincluded in the image data after the adjustment is performed.
 14. Amethod for controlling an apparatus, the method comprising: resolvinginput image data into image data for each frequency band; acquiringskewness corresponding to the resolved image data, wherein the skewnessis acquired from a histogram corresponding to each of the resolved imagedata; and determining image data to be processed, out of the resolvedimage data based on the acquired skewness, and performing gainadjustment on the determined image data.
 15. The method according toclaim 14, further comprising: synthesizing the input image data, theimage data obtained by performing gain adjustment on the image data tobe processed, out of the resolved image data, and the image data not tobe processed out of the resolved image data; and outputting thesynthesized image data.
 16. The method according to claim 14, whereinthe input image data is divided into optional regions, and the resolvingperforms resolving on each of the divided regions.
 17. A non-transitorystorage medium which stores a computer program for making a computerfunction as respective units of an apparatus, the apparatus comprising:a resolving unit configured to resolve input image data into image datafor each frequency band; an acquisition unit configured to acquireskewness corresponding to the resolved image data resolved by theresolving unit, wherein the skewness is acquired from a histogramcorresponding to each of the resolved image data; and an adjustment unitconfigured to determine image data to be processed, out of the resolvedimage data based on the acquired skewness and perform gain adjustment onthe determined image data.
 18. The non-transitory storage mediumaccording to claim 17, further comprising: synthesizing the input imagedata, the image data obtained by performing gain adjustment on the imagedata to be processed, out of the resolved image data, and the image datanot to be processed out of the resolved image data; and outputting thesynthesized image data.
 19. The non-transitory storage medium accordingto claim 17, wherein the input image data is divided into optionalregions, and the resolving performs resolving on each of the dividedregions.